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Use the CData ODBC Driver for Databricks to visualize Databricks data in Power BI Desktop.
With built-in support for ODBC on Microsoft Windows, the CData ODBC Drivers provide self-service integration with self-service analytics tools such as Microsoft Power BI. The CData ODBC Driver for Databricks links your Power BI reports to operational Databricks data. You can monitor Databricks data through dashboards and ensure that your analysis reflects Databricks data in real time by scheduling refreshes or refreshing on demand. This article details how to use the ODBC driver to create real-time visualizations of Databricks data in Microsoft Power BI Desktop and then upload to Power BI.
The CData ODBC Drivers offer unmatched performance for interacting with live Databricks data in Power BI due to optimized data processing built into the driver. When you issue complex SQL queries from Power BI to Databricks, the driver pushes supported SQL operations, like filters and aggregations, directly to Databricks and utilizes the embedded SQL Engine to process unsupported operations (often SQL functions and JOIN operations) client-side. With built-in dynamic metadata querying, you can visualize and analyze Databricks data using native Power BI data types.
About Databricks Data Integration
Accessing and integrating live data from Databricks has never been easier with CData. Customers rely on CData connectivity to:
- Access all versions of Databricks from Runtime Versions 9.1 - 13.X to both the Pro and Classic Databricks SQL versions.
- Leave Databricks in their preferred environment thanks to compatibility with any hosting solution.
- Secure authenticate in a variety of ways, including personal access token, Azure Service Principal, and Azure AD.
- Upload data to Databricks using Databricks File System, Azure Blog Storage, and AWS S3 Storage.
While many customers are using CData's solutions to migrate data from different systems into their Databricks data lakehouse, several customers use our live connectivity solutions to federate connectivity between their databases and Databricks. These customers are using SQL Server Linked Servers or Polybase to get live access to Databricks from within their existing RDBMs.
Read more about common Databricks use-cases and how CData's solutions help solve data problems in our blog: What is Databricks Used For? 6 Use Cases.
Getting Started
Connect to Databricks as an ODBC Data Source
If you have not already, first specify connection properties in an ODBC DSN (data source name). This is the last step of the driver installation. You can use the Microsoft ODBC Data Source Administrator to create and configure ODBC DSNs.
To connect to a Databricks cluster, set the properties as described below.
Note: The needed values can be found in your Databricks instance by navigating to Clusters, and selecting the desired cluster, and selecting the JDBC/ODBC tab under Advanced Options.
- Server: Set to the Server Hostname of your Databricks cluster.
- HTTPPath: Set to the HTTP Path of your Databricks cluster.
- Token: Set to your personal access token (this value can be obtained by navigating to the User Settings page of your Databricks instance and selecting the Access Tokens tab).
Create Data Visualizations
After creating an ODBC DSN, follow the steps below to connect to the Databricks ODBC DSN from Power BI Desktop:
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Open Power BI Desktop and click Get Data -> More... to open the Get Data window.
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In the Get Data window select Other -> ODBC to open the next window.
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Select the DSN in the menu. If you know the SQL query you want to use to import data, you can expand the Advanced options node and enter the query in the SQL Statement box. Otherwise, click OK to continue.
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Choose Default or Custom as the authentication option and click Connect.
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Select tables in the Navigator dialog.
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Click Transform Data to edit the query. The table you imported is displayed in the Power Query Editor. In the Power Query Editor, you can enrich your local copy of Databricks data with other data sources, pivot Databricks columns, and more. Power BI detects each column's data type from the Databricks metadata retrieved by the driver.
Power BI records your modifications to the query in the Applied Steps section, adjusting the underlying data retrieval query that is executed to the remote Databricks data. When you click Close and Apply, Power BI executes the data retrieval query.
Otherwise, click Load to pull the data into Power BI.
Create Data Visualizations
After pulling the data into Power BI, you can create data visualizations in the Report view by dragging fields from the Fields pane onto the canvas. Follow the steps below to create a pie chart (Salesforce shown):
- Select the pie chart icon in the Visualizations pane.
- Select a dimension in the Fields pane: for example, Name.
- Select a measure in the Fields pane: for example, Annual Revenue.

You can change sort options by clicking the ellipsis (...) button for the chart. Options to select the sort column and change the sort order are displayed.
You can use both highlighting and filtering to focus on data. Filtering removes unfocused data from visualizations; highlighting dims unfocused data. You can highlight fields by clicking them:

You can apply filters at the page level, at the report level, or to a single visualization by dragging fields onto the Filters pane. To filter on the field's value, select one of the values that are displayed in the Filters pane.

Click Refresh to synchronize your report with any changes to the data.
Free Trial & More Information
If you are interested in connecting to your Databricks data from Microsoft Power BI, or any applications that support ODBC connectivity, download a free, 30-day trial of the CData ODBC Driver for Databricks. As always, our world-class support team is ready to answer any questions you may have.